Project Summary

Project summary

Goals

Findings

Analysis & findings

Data Overview

Twitter data

Twitter data was obtained freely through a partnership between UCSB Library and Crimson Hexagon. Before downloading, the data was queried to meet the following conditions:

  1. Tweet came from the Santa Barbara area (add more details about how CH applies the location query)
  2. Only original tweets (no retweets)
  3. Date was marked between January 1, 2015 and December 31, 2019

Crimson Hexagon only allows 10,000 randomly selected tweets to be exported, manually, at a time in .xls format. Due to this restriction, data was manually downloaded for every 2 days in order to capture all tweets. There were around 5000 average number of daily tweets that met these conditions.

The Crimson Hexagon data did not contain all desired information, including whether or not the tweet was geotagged. To get this information we used the python twarc library to “rehydrate” the data using individual tweet ids and store the tweet information as .json files. From here we were able to remove all tweets that did not have a geotag, giving us a total of 82,876 tweets.

Table of data

Here is a sample of the type of the final twitter information we obtained.

created_at tweet_id full_text user_id user_location geo_type geo_coordinates language retweet_count favorite_count lat lon
Thu Oct 25 15:11:03 +0000 2018 1.055477e+18 #tbt to five years ago today… 🎉 Flutter Magazine Issue No. 1 was hot off the press in Santa Barbara, California. It’s been a whirlwind 5 years of beautiful, creative, inspiring,… https://t.co/EdTLt2GgWb 1252883832 Los Angeles, CA Point c(34.4258, -119.714) en 0 1 34.42580 -119.7140
Sat Jul 16 03:38:59 +0000 2016 7.541584e+17 Just posted a photo @ Santa Barbara County Courthouse https://t.co/MF508KDQJM 136403690 U.S.A, CA, Santa Barbara. Point c(34.42435, -119.702461) en 0 0 34.42435 -119.7025
Fri May 08 18:29:38 +0000 2015 5.967438e+17 Mama 2 years ago today we said goodbye to you, missing you doesn’t get easier but I thank you & God… https://t.co/wOEYZ8uZlv 362204954 Ventura, California Point c(34.38814401, -119.51557072) en 0 0 34.38814 -119.5156
Tue Feb 07 20:41:18 +0000 2017 8.290675e+17 Staring this Friday, Feb. 10 we will be celebrating Valentine’s Day all weekend long at… https://t.co/PfPwMpJPTG 2683395770 131 Anacapa Street, Suite C Point c(34.41468768, -119.69030981) en 0 0 34.41469 -119.6903
Sun Apr 16 18:10:02 +0000 2017 8.536718e+17 Just uploaded 1 new photo to my Flickr “Project 365 - 2017” photoset: https://t.co/57o9JQRfZu https://t.co/afxuApScUE 35313007 Santa Barbara, CA USA Point c(34.4239533, -119.705) en 0 0 34.42395 -119.7050
Fri Sep 23 01:56:06 +0000 2016 7.791372e+17 Baby’s toes touch the ocean for the 1st time! Maybe it’s a little too cold mom! @ Carpinteria… https://t.co/CP78rpyODP 44481856 Los Angeles, CA Point c(34.39361076, -119.52207238) en 0 0 34.39361 -119.5221
Tue Sep 22 20:27:41 +0000 2015 6.464206e+17 Pink petal portrait of a pal. @ Los Arroyos https://t.co/1FBxohUqlW 575553178 Fort Worth, TX. Point c(34.4216499, -119.6411819) en 0 0 34.42165 -119.6412
Tue Apr 14 22:48:57 +0000 2015 5.881117e+17 I don’t feel like a freshman 156529750 Santa Barbara, CA Point c(34.41214016, -119.85574636) en 0 1 34.41214 -119.8557
Thu Oct 31 19:38:33 +0000 2019 1.189990e+18 Have you downloaded our mobile app yet? Been getting amazing feedback! Easily book haircuts and earn stamps for free stuff you already love buying. Free pomades, headwear t-shirts and more! Link is in our bio.… https://t.co/gOMHMlXRme 2831364296 27 1/2 E Vivtoria St. Santa Barbara CA Point c(34.42940389, -119.86914428) en 0 0 34.42940 -119.8691
Thu Apr 06 15:33:08 +0000 2017 8.500085e+17 Oh and all art is 15% off!! #homeiswheretheartis @ Clothesline… https://t.co/oxflNojb3d 23015697 santa barbara Point c(34.3987999, -119.5188217) en 0 0 34.39880 -119.5188

The spatial distribution of tweets highlights areas of higher population density and tourist areas in downtown Santa Barbara. There is a single coordinate that has over 11,000 tweets reported across all years. It is near De La Vina between Islay and Valerio. There is nothing remarkable about this site so I assume it is the default coordinate when people tag “Santa Barbara” generally. The coordinate is 34.4258, -119.714.

Interactive map with cluster markers

As you zoom in on the map, clusters will disaggregate. You can click on blue points to see the tweet.

Tweet density

This is log-transformed.

Tourists and locals

This project aims to understand if and how preferences differ between tourists and locals for nature-based places within the Santa Barbara area. In order to test this we needed to come up with a way to identify tourists or locals. We used a two step process.

First, if the user has self-identified their location as somewhere in the Santa Barbara area, they are designated a local. This includes Carpinteria, Santa Barbara, Montecito, Goleta, Gaviota and UCSB. For the remainder, we use the number of times they have tweeted from Santa Barbara within a year to designate user type. If someone has tweeted across more than 2 months in the same year from Santa Barbara, they are identified as a local. This is consistent with how Eric Fischer determined tourists in his work. This is not fool-proof and there are instances were people visit and tweet from Santa Barbara more than two months a year, especially if they are visiting family or live within a couple hours driving distance.

There are 26408 tweets from tourists and 56468 tweets from locals.

The following map shows tweet log density by locals (top - blue) and tourists (bottom - red).

Nature-based tweets

The full text of each tweet was analyzed to be either nature-based or not. We developed a coarse dictionary of words that indicate a nature-based tweet. These include natural features like ocean, coast, park, and works that indicate recreating (fishing, hiking, camping, etc.).

Note I had a hard time finding an ontology or lexicon that would fit this project. These are definitely skewed more towards nature and recreation rather than words like “home” or “connection”.

##  [1] "hike"        "trail"       "hiking"      "camping"     "tent"       
##  [6] "climb"       "summit"      "fishing"     "sail"        "sailing"    
## [11] "boat"        "boating"     "ship"        "cruise"      "cruising"   
## [16] "bike"        "biking"      "dive"        "diving"      "surf"       
## [21] "surfing"     "paddle"      "swim"        "ocean"       "beach"      
## [26] "^sea"        "sand"        "coast"       "island"      "wave"       
## [31] "fish"        "whale"       "dolphin"     "pacific"     "crab"       
## [36] "lobster"     "water"       "shore"       "marine"      "seawater"   
## [41] "lagoon"      "slough"      "saltwater"   "underwater"  "tide"       
## [46] "aquatic"     "^tree"       "^earth"      "weather"     "sunset"     
## [51] "sunrise"     "^sun"        "climate"     "park"        "wildlife"   
## [56] "^view"       "habitat"     "^rock"       "nature"      "mountains"  
## [61] "^peak"       "canyon"      "pier"        "wharf"       "environment"
## [66] "ecosystem"

Let’s look at some examples of what tweets qualified as “nature-based”.

Month Day Time Year full_text user_id user_location geo_coordinates retweet_count favorite_count lat lon month_num date user_type nature_word
Mar 29 01:30:46 2015 hanging out with my peers #nolananddella @ elephant seal beach https://t.co/kr3mmmozsu 531880592 San Francisco, CA c(34.40982283, -119.68535927) 0 0 34.40982 -119.6854 3 2015-03-29 tourist 1
Jun 10 02:40:25 2016 i’m at fess parker’s doubletree resort in santa barbara, ca https://t.co/3u6hdmck2h 13314962 iPhone: 34.016556,-118.403152 c(34.41691647, -119.677063) 0 1 34.41692 -119.6771 6 2016-06-10 local 1
Aug 19 20:46:34 2019 another successful #sundayfunday yesterday as the race for the @flysivlerair @poloassociation pacific coast open trophy continues! 🏆 the results for this weekend are in.. fmb too! defeated lucchese 12-9,… https://t.co/lnqkvxvklg 44967234 Santa Barbara, CA c(34.41831875, -119.56351644) 0 1 34.41832 -119.5635 8 2019-08-19 local 1
Jul 3 02:40:52 2015 concerts in the park! with the long run, an eagles cover band! #santabarbara #sunset #california… https://t.co/ratz2nqfvc 931090388 Santa Barbara, CA, USA c(34.4149762, -119.68390284) 0 1 34.41498 -119.6839 7 2015-07-03 local 1
Sep 20 20:33:32 2016 sneak peak from vanessasuarezactress and isiat’s beach wedding on sunday! such a fun day with… https://t.co/6ytg4txile 228593361 Los Angeles, CA c(34.4258, -119.714) 0 0 34.42580 -119.7140 9 2016-09-20 tourist 1
Mar 26 18:30:02 2016 tranche de states. no heel shoes on the santa barbara beach and pier. #santabarbara #advertising… https://t.co/xzfhixljli 2797908051 Amiens, Picardie c(34.4258, -119.714) 0 0 34.42580 -119.7140 3 2016-03-26 tourist 1
May 4 01:52:02 2019 strawberry shortcake #childhoodmemories at the miramar club only… sneak peek.. harrysberries of course! @ rosewood miramar beach https://t.co/hagomhmblm 71301801 Montecito, CA c(34.42066, -119.6286) 0 0 34.42066 -119.6286 5 2019-05-04 local 1
Sep 5 21:45:43 2016 i’m at leadbetter beach & park in santa barbara, ca w/ @bpineda https://t.co/irigggktyo https://t.co/p3jtsoambk 18778505 Silicon Valley, CA c(34.40238282, -119.69907649) 0 1 34.40238 -119.6991 9 2016-09-05 tourist 1
Sep 23 20:46:44 2016 cruised down the pacific coast highway, then cruised on this bad boy… https://t.co/o6ptpjvybt 84445081 NA c(34.4258, -119.714) 0 0 34.42580 -119.7140 9 2016-09-23 tourist 1
Dec 24 17:29:47 2016 it’s a glorious morn 🌟merry christmas eve day #santabarbara #christmaseve ##seesb #islands 💨🌤day… https://t.co/tsmzhqfble 135408044 Santa Barbara, CA c(34.4258, -119.714) 0 0 34.42580 -119.7140 12 2016-12-24 local 1
Jun 11 21:29:36 2016 craft brew circus maria c. nick b. lori b. - drinking a vortex ipa @ chase palm park - https://t.co/n6pyutm8fj #photo 52174270 iPhone: 34.227627,-119.182358 c(34.4147, -119.683) 1 1 34.41470 -119.6830 6 2016-06-11 local 1
Mar 18 00:10:29 2016 the slough at hendry’s beach, #santabarbara. #travel @ hendry’s off leash dog beach https://t.co/v09erfdtom 137462549 Santa Barbara c(34.4023018, -119.74191313) 0 1 34.40230 -119.7419 3 2016-03-18 local 1
Apr 20 17:58:05 2015 beach burn day 1!!! it was awesome! #santabarbara #fitlife #fitness #mondaymotivation http://t.co/8bccvohlnv 3093801122 Santa Barbara, CA c(34.42160436, -119.6902323) 0 0 34.42160 -119.6902 4 2015-04-20 local 1
Aug 23 02:13:19 2018 i forget how close this calm is 😍 @ carpinteria state beach https://t.co/6uvvntmkrx 1035418338 NA c(34.39361076, -119.52207238) 0 0 34.39361 -119.5221 8 2018-08-23 local 1
Jun 8 19:12:51 2019

getting in these cali streets while we got sunny weather today. ☀️🌴

what y’all getting into today? @ santa barbara, california https://t.co/9sefvjbcpz 		37780090 Los Angeles c(34.4258, -119.714) 0 0 34.42580 -119.7140 6 2019-06-08 tourist 1
Jun 8 00:35:08 2019 paulyoz works the magic. pacific octopus, borlotti, taleggio, pickled romano and pixie ojai valley tangerine 👊 caruso #tonight @ rosewood miramar beach https://t.co/5aav3avzli 71301801 Montecito, CA c(34.42066, -119.6286) 0 0 34.42066 -119.6286 6 2019-06-08 local 1
Oct 19 21:34:16 2018 sailing away. . more crazy clouds and a brilliant sunset. i took this earlier this year when we were doing some camp hosting just north of santa barbara. we’d sneak down into town sometimes… https://t.co/kbfbnav6aj 35854622 Alaska c(34.4258, -119.714) 0 0 34.42580 -119.7140 10 2018-10-19 tourist 1
Jul 10 17:35:17 2016 casualties of “natural seepage,” as the “scientists” call it. #offshoredrilling #sandtar… https://t.co/ogjrswbtjc 3460872133 Los Angeles c(34.4040308, -119.7301866) 0 0 34.40403 -119.7302 7 2016-07-10 tourist 1
Aug 3 19:27:23 2015 yesterday’s epic jenga shenanigans with the sandy crew #latergram #doyouevenjengabro 😜🍻 @ pure… https://t.co/qricczwezd 28525364 West Hollywood, CA c(34.4237518, -119.6865692) 0 0 34.42375 -119.6866 8 2015-08-03 local 1
Aug 6 16:12:34 2015 those vibrant days on the coast… #california #santabarbara #montecito #pacific #ocean #beach @… https://t.co/wylcmqbs16 353576024 Santa Barbara, CA c(34.41706346, -119.64480638) 0 0 34.41706 -119.6448 8 2015-08-06 local 1

Where are nature-based tweets?

After identifying nature-based tweets we can take a look at where these tweets are coming from and compare to the general pattern of tweets.

Who is tweeting nature-based tweets?

Not surprisingly there are less nature-based tweets than nature-based. Of all tweets, % are nature-based.

Of local tweeters, 13.7643962% of tweets are nature-based. Of tourists, 21.716904% are nature-based.

Are tweets in protected areas more often nature-based?

California Protected Areas Database

We can use the CPAD data to identify protected areas. [expandon CPAD here]

How many tweets come from these areas?

Count how many points in each polygon (all types of tweets not just nature based)

Some of these areas overlap with high tourist areas (e.g. the Bowl, Zoo and Wharf). Let’s look at the content of these tweets to see how often tweets coming from these locations are nature-based or not.

Compare occurrence of nature vs non-nature based tweets

The highest ratio of nature tweets to non-nature takes place at Manning Park.

Let’s look at the top 20 most popular sites

Not surprisingly the Santa Barbara Bowl has the most number of tweets, but only half are nature based (the view is great!). If we just look at proportion of nature-based tweets we see a different ordering. I removed any places with just 1 tweet since it will skew results if that tweet happens to be nature-based (a total of 4 places).

How does this differ across tourists and locals?

Looking at the breakdown between tourists and locals. The sites included here have at least 50 tweets total across the time frame.

Time

Timeline of tweets

Initial hypothesis was identifying spikes in nature-based tweets around three significant events: - Refugio oil spill in 2015 - Thomas fire in 2017 - Debris flow in 2018

Word clouds

top 100 words for locals vs tourist. And we could do this in space. At sterns wharf what are people tweeting about? At Elings, what are locals tweeting about?

Maybe in word clouds we can see some changes due to natural events

All of SB

By area

Sentiment Analysis

Lessons learned

Data is harder to find

Future research

Looking at different scale areas

There might be an interesting comparison between rural-suburban-urban areas. We hypothseize that the tourist/local alignment would split in urban areas, maybe aligned in suburban (like SB) and maybe not exist in rural.

Proportion of words that are nature based tells you how people. In Santa Barbara, there will be a lot of nature-based sense of place. In Manhattan, we wouldn’t expect to see nature based ones so much.

In a blog piece we can pose questions that we couldn’t answer but stuff like “can proportion of tourists/locals in place engagement tell us anything”.

Could compare % nature based tweets in SB to other areas. If we did this across the whole state, what proportion% are nature based? Maybe on average its just 5%.

Where and why do locals and tourists overlap in their use of area. SB seems to have a high alignment of tourists/locals, which may be helpful for local policy. Maybe places with distinct differences in how tourists/locals use places.

Look at cities of different coastal sizes rural - small town - urban - mega city. Could see how tourists/locals patterns differentiate across scale.

Is there a threshold of tourists where locals don’t go anymore?

In areas where we see both tourists and locals engaging, what characteristics do we see?

Quantifying transitions between rural to city.

Talk about overall social media literature for conservation and how this project is similar/different and used lessons from those papers to guide this analysis.